Quantitative Analysis of Finance II (ECON90010)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

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Semester 1
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The subject will focus on estimating and testing nonlinear models in finance including volatility models, artificial neural networks, factor models of contagion and discrete models of financial behaviour. Special attention will be given to estimating and testing dynamic latent factor models using Principal Components and Kalman filters, modelling risk neutral dynamics in option markets, and fat-tailed behaviour in asset returns using extreme value theory and copulas. Estimation and testing methods are based on maximum likelihood methods. The R, RStudio and Excel computer programs will be used throughout the course. This subject also provides students with the experience of carrying out a research-based project on a specific topic in applied econometrics.

Intended learning outcomes

On successful completion of this subject students should be able to:

  • Identify and apply recent advances in quantitative methods to solve a range of problems in finance.
  • Describe how quantitative procedures can be applied in financial decision making.
  • Demonstrate a sophisticated understanding of quantitative methods by reproducing existing results. This will involve using both mathematical and computer skills. The computer programs used are R, RStudio and Excel.
  • Develop alternative frameworks for exploring new ideas in building alternative financial models.
  • Evaluate the strengths and importance of research in applied finance and the implications of research for solving financial problems.
  • Complete a written research report.

Generic skills

On successful completion of this subject, students should have improved the following generic skills:

  • Evaluation of ideas, views and evidence;
  • Synthesis of ideas, views and evidence;
  • Strategic thinking;
  • Critical thinking;
  • Application of theory to economic policy and business decision making;
  • Summary and interpretation of information;
  • Statistical reasoning;
  • Problem solving skills;
  • Written communication; and
  • Oral communication.

Last updated: 8 November 2024